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Effect of skin-capsular distance on controlled attenuation parameter for diagnosing liver steatosis in patients with nonalcoholic fatty liver disease.

ABSTRACT: The effect of the skin-capsular distance (SCD) on the controlled attenuation parameter (CAP) for diagnosis of liver steatosis in patients with nonalcoholic fatty liver disease (NAFLD) remains unclear. The SCD was measured using B-mode ultrasound, and the CAP was measured using the M probe of FibroScan^®. According to the indications of the M probe, 113 patients with an SCD of ≤ 25 mm were included in the present study. The association between the SCD and CAP was investigated, and the diagnostic performance of the SCD-adjusted CAP was tested. The SCD showed the most significant positive correlation with the CAP (ρ = 0.329, p < 0.001). In the multiple regression analysis, the SCD and serum albumin concentration were associated with the CAP, independent of pathological liver steatosis. According to the multivariate analysis, two different formulas were developed to obtain the adjusted CAP using the SCD and serum albumin concentration as follows: adjusted CAP (dB/m) = CAP - (5.26 × SCD) and adjusted CAP (dB/m) = CAP - (5.35 × SCD) - (25.77 × serum albumin concentration). The area under the receiver operating characteristic curve for diagnosis of a steatosis score ≥ 2 of adjusted CAP was 0.678 and 0.684 respectively, which were significantly greater than the original CAP (0.621: p = 0.030 and p = 0.024). The SCD is associated with the CAP independent of liver steatosis. Adjustment of the CAP using the SCD improves the diagnostic performance of the CAP in NAFLD.

SUBMITTER: Kimura S

PROVIDER: S-EPMC8329228 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Effect of skin-capsular distance on controlled attenuation parameter for diagnosing liver steatosis in patients with nonalcoholic fatty liver disease.

Kimura Syunichiro S Tanaka Kenichi K Oeda Satoshi S Inoue Kaori K Inadomi Chika C Kubotsu Yoshihito Y Yoshioka Wataru W Okada Michiaki M Isoda Hiroshi H Kuwashiro Takuya T Akiyama Takumi T Kurashige Aya A Oshima Ayaka A Oshima Mayumi M Matsumoto Yasue Y Kawaguchi Atsushi A Anzai Keizo K Sueoka Eisaburo E Aishima Shinichi S Takahashi Hirokazu H

Scientific reports 20210802 1

The effect of the skin-capsular distance (SCD) on the controlled attenuation parameter (CAP) for diagnosis of liver steatosis in patients with nonalcoholic fatty liver disease (NAFLD) remains unclear. The SCD was measured using B-mode ultrasound, and the CAP was measured using the M probe of FibroScan<sup>®</sup>. According to the indications of the M probe, 113 patients with an SCD of ≤ 25 mm were included in the present study. The association between the SCD and CAP was investigated, and the d ...[more]

PMID: 34341368

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Project description:BackgroundThe consistency in steatosis grading between magnetic resonance imaging-based proton density fat fraction (MRI-PDFF) and controlled attenuation parameter (CAP) before and after treatment remains unclear. This study aimed to compare the diagnostic accuracy of steatosis grading between MRI-PDFF and CAP using liver biopsy as standard and to evaluate the value of monitoring changes in steatosis grading with CAP during follow-up utilizing MRI-PDFF as a reference.MethodsConsecutive patients from a biopsy cohort and a randomized controlled trial were included in this study and classified into 3 groups (the biopsy, orlistat treatment, and routine treatment subgroups). Hepatic steatosis was measured via MRI-PDFF and CAP at baseline and at the 6th month; the accuracy and cutoffs were assessed in the liver biopsy cohort at baseline.ResultsA total of 209 consecutive patients were enrolled. MRI-PDFF and CAP showed comparable diagnostic accuracy for detecting pathological steatosis [⩾S1, area under the receiver operating characteristic curve (AUC) = 0.984 and 0.972, respectively]; in contrast, CAP presented significantly lower AUCs in grades S2-3 and S3 (0.820 and 0.815, respectively). The CAP values correlated well with the MRI-PDFF values at baseline and at the 6th month (r = 0.809 and 0.762, respectively, both p < 0.001), whereas a moderate correlation in their changes (r = 0.612 and 0.524 for moderate-severe and mild steatosis, respectively; both p < 0.001) was observed. The AUC of CAP change was obtained to predict MRI-PDFF changes of ⩾5% and ⩾10% (0.685 and 0.704, p < 0.001 and p = 0.001, respectively). The diagnostic agreement of steatosis grade changes between MRI-PDFF and CAP was weak (κ = 0.181, p = 0.001).ConclusionsCAP has decreased value for the initial screening of moderate-severe steatosis and is limited in monitoring changes in steatosis during treatment. The confirmation of steatosis grading with MRI-PDFF remains necessary.

Project description:BackgroundNonalcoholic fatty liver disease (NAFLD) is recognized as one of the most common chronic liver diseases worldwide. This study aims to assess the efficacy of automated machine learning (AutoML) in the identification of NAFLD using a population-based cross-sectional database.MethodsAll data, including laboratory examinations, anthropometric measurements, and demographic variables, were obtained from the National Health and Nutrition Examination Survey (NHANES). NAFLD was defined by controlled attenuation parameter (CAP) in liver transient ultrasound elastography. The least absolute shrinkage and selection operator (LASSO) regression analysis was employed for feature selection. Six algorithms were utilized on the H2O-automated machine learning platform: Gradient Boosting Machine (GBM), Distributed Random Forest (DRF), Extremely Randomized Trees (XRT), Generalized Linear Model (GLM), eXtreme Gradient Boosting (XGBoost), and Deep Learning (DL). These algorithms were selected for their diverse strengths, including their ability to handle complex, non-linear relationships, provide high predictive accuracy, and ensure interpretability. The models were evaluated by area under receiver operating characteristic curves (AUC) and interpreted by the calibration curve, the decision curve analysis, variable importance plot, SHapley Additive exPlanation plot, partial dependence plots, and local interpretable model agnostic explanation plot.ResultsA total of 4177 participants (non-NAFLD 3167 vs NAFLD 1010) were included to develop and validate the AutoML models. The model developed by XGBoost performed better than other models in AutoML, achieving an AUC of 0.859, an accuracy of 0.795, a sensitivity of 0.773, and a specificity of 0.802 on the validation set.ConclusionsWe developed an XGBoost model to better evaluate the presence of NAFLD. Based on the XGBoost model, we created an R Shiny web-based application named Shiny NAFLD (http://39.101.122.171:3838/App2/). This application demonstrates the potential of AutoML in clinical research and practice, offering a promising tool for the real-world identification of NAFLD.

Dataset Information

Effect of skin-capsular distance on controlled attenuation parameter for diagnosing liver steatosis in patients with nonalcoholic fatty liver disease.

Publications

Effect of skin-capsular distance on controlled attenuation parameter for diagnosing liver steatosis in patients with nonalcoholic fatty liver disease.

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